Disaggregation of humanitarian data by disability: a realist evaluation of the use of the Washington Group Questions to support more inclusive practices

Abstract

Abstract People with disabilities make up approximately 16% of the world’s population and disproportionately experience the risks and negative impacts of humanitarian emergencies. In humanitarian contexts, understanding who has a disability, where they are located, and what their needs are is crucial to delivering the right assistance at the right place and time. In recent years, global attention to disability inclusion in the humanitarian sector has focused on the generation of disaggregated data, most commonly using one of the Washington Group Sets of Questions. The implicit assumption behind the collection of more and more data disaggregated by disability, that it will lead to more inclusive action and outcomes, is incorrect. Our findings nuance the current push for disability disaggregated data in all settings and advocate a shift away from the blanket application of disaggregation to a more bespoke approach. Humanitarian and development contexts present multiple challenges to disaggregating data sets by demographic factors such as disability, including the use of households rather than individuals as the unit of analysis, small and non-representative samples, and minority languages with limited translation capacity. Through evaluation of the use of the Washington Group set across the world’s largest humanitarian organization, and its cooperating partners, we present five decision-making criteria that can be flexibly but consistently applied across operating contexts. This enables contextualized decision-making that uses consistent logic to predict the likelihood of data disaggregation by disability leading to more inclusive action and outcomes.

Keywords

• Disability
• Inclusion
• Humanitarian
• Data disaggregation
• Data
• Food security